The present invention relates generally to systems utilizing locally collected sound data corresponding to ultrasound emissions from distributed electromechanical equipment, and providing remote and centralized fault detection analysis. More particularly, embodiments of an invention as disclosed herein relate to systems for auto-generation of a new equipment configuration and associated inspection points based on make and model number matching algorithms and using extracted equipment configuration information from a hosted database.
Certain systems are conventionally known for the purpose of diagnosing electromechanical equipment in the field using ultrasound collection, for example in order to provide predictive maintenance services. However, it is generally inefficient to have highly trained technicians personally travel to each location in order to perform diagnostics. Mechanical contractors, service providers, and the like generally struggle to find and train qualified technicians, such that the availability for trained technicians is accordingly scarce, and efficient resource allocation is critical. Therefore, various systems have been implemented to locally collect sound data and engage a centrally located technician (i.e., remote with respect to the equipment itself) to manually diagnose the sounds of the equipment, or in some cases to even automate the diagnostics process based on stored data files corresponding to the sounds produced by the equipment.
In either case, it is important to have adequate knowledge regarding the equipment configuration. However, property equipment lists at both property managers/owners and HVAC service companies are not readily available. Alternative equipment lists tend to be incomplete and/or inaccurate, and the relevant information is difficult for inexperienced personnel to gather. Generally stated, identifying specific sub-components of a specific unit for configuration purposes requires scarce technical knowledge and is a time-consuming manual process. Examples of configuration information that may therefore be unavailable without the presence of experienced personnel onsite could include one or more of the equipment name, description, system type, make, model, serial number, and the like.
The lack of accurate knowledge regarding an equipment configuration can be more than a barrier to effective diagnostics, but may present a barrier in winning or maintaining business. Incomplete or incorrect data entered into a quote or otherwise describing equipment configuration may cause significant rework and potential loss of margin.